Created in 2012, Gartner's "Analytics Maturity Model" is a staple of many analytical discussions. As you move from Descriptive Analytics (Level 1) to the most advanced stage, Prescriptive Analytics (Level 4), you may believe all past techniques for deriving data driven insights are obsolete. Predictive Analytics (Level 3) techniques have been used in talent development for decades via psychometric assessments.
I recently attended a virtual analytics summit featuring specialists from leading consulting firms, Visier and Tech Data. Session panelists described the important roles Industrial/Organizational (I/O) Psychologists and Statisticians play in the analytics space. I/O Psychology and Statistics are also the backbone of the assessment industry. The same statistical analysis techniques, such as T-Tests or ANOVA analysis, are used when creating assessment models.
Companies can easily add predictive insights to any data driven people project. Using a valid and reliable assessment can instantly provide answers to the question predictive analytics seeks to answer, "What could happen in the future?".
To provide an example, you may find yourself working on a succession planning initiative to identify and develop future leaders within your organization. You then choose a quality psychometric assessment that measures General Mental Ability (GMA) and personality. Better still, you have a validated senior leader model benchmarked against a large population of successful senior leaders. You can now assess your pipeline of potential leaders and predict who likely has the best chance of success in the future. That is predictive analytics at work using psychometrics.
In reality, life doesn't always fit into neat categories. Just focus on tools that help you organize, summarize, and interpret insightful meaning. Each phase of the analytics maturity model matters and plays out differently depending on the questions you are trying to answer with data. Sometimes the best methods and answers are already right in front of you.
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